Assessing the impact of including variation in general population mortality on standard errors of relative survival and loss in life expectancy.

BACKGROUND: A relative survival approach is often used in population-based cancer studies, where other cause (or expected) mortality is assumed to be the same as the mortality in the general population, given a specific covariate pattern. The population mortality is assumed to be known (fixed), i.e. measured without uncertainty. This could have implications for the estimated standard errors (SE) of any measures obtained within a relative survival framework, such as relative survival (RS) ratios and the loss in life expectancy (LLE). We evaluated the existing approach to estimate SE of RS and the LLE in comparison to if uncertainty in the population mortality was taken into account. METHODS: The uncertainty from the population mortality was incorporated using parametric bootstrap approach. The analysis was performed with different levels of stratification and sizes of the general population used for creating expected mortality rates. Using these expected mortality rates, SEs of 5-year RS and the LLE for colon cancer patients in Sweden were estimated. RESULTS: Ignoring uncertainty in the general population mortality rates had negligible (less than 1%) impact on the SEs of 5-year RS and LLE, when the expected mortality rates were based on the whole general population, i.e. all people living in a country or region. However, the smaller population used for creating the expected mortality rates, the larger impact. For a general population reduced to 0.05% of the original size and stratified by age, sex, year and region, the relative precision for 5-year RS was 41% for males diagnosed at age 85. For the LLE the impact was more substantial with a relative precision of 1286%. The relative precision for marginal estimates of 5-year RS was 3% and 30% and for the LLE 22% and 313% when the general population was reduced to 0.5% and 0.05% of the original size, respectively. CONCLUSIONS: When the general population mortality rates are based on the whole population, the uncertainty in the estimates of the expected measures can be ignored. However, when based on a smaller population, this uncertainty should be taken into account, otherwise SEs may be too small, particularly for marginal values, and, therefore, confidence intervals too narrow.

Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study.

INTRODUCTION: Individual case reports are the main asset in pharmacovigilance signal management. Signal validation is the first stage after signal detection and aims to determine if there is sufficient evidence to justify further assessment. Throughout signal management, a prioritization of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in pharmacoepidemiological studies to assess communicated signals. OBJECTIVE: The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process. METHODS: Statistical signal detection was performed in VigiBase, the WHO global database of individual case safety reports, targeting generic manufacturer drugs and 16 prespecified adverse events. During a 5-day study-a-thon, signal validation and prioritization were performed using information from VigiBase, regulatory documents and the scientific literature alongside descriptive analyses of routine health data from 10 partners of the European Health Data and Evidence Network (EHDEN). Databases included in the study were from the UK, Spain, Norway, the Netherlands and Serbia, capturing records from primary care and/or hospitals. RESULTS: Ninety-five statistical signals were subjected to signal validation, of which eight were considered for descriptive analyses in the routine health data. Design, execution and interpretation of results from these analyses took up to a few hours for each signal (of which 15-60 minutes were for execution) and informed decisions for five out of eight signals. The impact of insights from the routine health data varied and included possible alternative explanations, potential public health and clinical impact and feasibility of follow-up pharmacoepidemiological studies. Three signals were selected for signal assessment, two of these decisions were supported by insights from the routine health data. Standardization of analytical code, availability of adverse event phenotypes including bridges between different source vocabularies, and governance around the access and use of routine health data were identified as important aspects for future development. CONCLUSIONS: Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost-benefit of integrating these analyses at this stage of signal management requires further research.

Remdesivir in the COVID-19 Pandemic: An Analysis of Spontaneous Reports in VigiBase During 2020.

INTRODUCTION: The safety profile of remdesivir, conditionally approved for COVID-19, was limited at its 2020 introduction. Adverse drug reactions (ADRs) for medicines are collected in VigiBase, the WHO Global Database of Individual Case Safety Reports (ICSRs). OBJECTIVE: This study aimed to provide a descriptive analysis of COVID-19 ICSR data focusing on remdesivir, including a disproportionality analysis (DA) of ADRs. METHODS: A dedicated algorithm enabled retrieval of all COVID-19 treatment-specific ICSRs. A severity algorithm based on co-reported medicines and symptoms enabled selection of tocilizumab with its well established safety profile as comparator for remdesivir. Descriptive statistics were used for general ICSR demographics for all COVID-19-specific medicines, remdesivir and tocilizumab individually and furthermore to present treatment patterns of medicines co-reported with remdesivir. A COVID-19 indication-focused DA was deployed to minimize confounding from underlying polysymptomatic disease. RESULTS: 14,574 COVID-19-related ICSRs were entered into VigiBase during 2020. Remdesivir was the most common medicine reported. Of 4944 remdesivir ICSRs, where tocilizumab was not co-reported, 93% described remdesivir as the sole suspect medicine. Sixty percent of ICSRs concerned males, median age was 63 years and the majority originated from the Americas (72%). In 1089 (21%) of remdesivir ICSRs, data indicated severe/critical disease. Co-reported medicines peaked during the first 3 days of remdesivir treatment. The DA for the established tocilizumab and the new remdesivir were mainly in line with the safety profiles for both medicines but suggested new safety concerns. The most reported ADRs for remdesivir represented liver dysfunction, kidney injury, death and bradycardia. CONCLUSION: Global COVID-19-related ADR reporting proved useful in providing information on ADRs as well as on treatment patterns in this patient group. Indication-focused disproportionality analysis, together with the use of a comparator with a known safety profile, proved effective in identifying known safety information and suggested new safety concerns for remdesivir.

Time spent in hormone-sensitive and castration-resistant disease states in men with advanced prostate cancer, and its health economic impact: registry-based study in Sweden.

OBJECTIVE: To investigate time spent in hormone-sensitive and castration-resistant disease states in men with advanced prostate cancer in Sweden, and the associated health economic impact. MATERIALS AND METHODS: Registry study (NCT03619980) of the Prostate Cancer data Base Sweden with data from the National Prostate Cancer Register, including the Patient-overview Prostate Cancer (PPC) and other national healthcare registries. The primary endpoint was time in each disease state. Secondary endpoints were co-medications, comorbidities and healthcare resource utilization (HRU) and cost in each disease state. RESULTS: In total, 1,869 men with advanced prostate cancer registered in PPC between 2014 and 2016, with data on the start of androgen deprivation therapy, were identified. Median time to progression and median survival were 4 and 11 years, respectively, for men with non-metastatic (nm) hormone-sensitive prostate cancer (HSPC); 1 and 7 years for men with metastatic (m) HSPC; and 1 and 8.5 years for men with nm castration-resistant prostate cancer (CRPC). Median survival for men with mCRPC was 4 years. Total annual mean costs for HRU per patient increased with increasing severity of disease, from 41,064 Swedish krona (SEK) for nmHSPC to 288,242 SEK for mCRPC. CONCLUSION: Progression time from mHSPC and nmCRPC to the mCRPC state was short and survival in the mCRPC state was approximately 4 years. Survival times were longer than expected, likely due to the selection of long-term survivors among prevalent cases. Healthcare costs were high for men with mCRPC. Further studies are needed to confirm our pilot study findings.